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Evidence record 191 · automatically gathered

CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models often fail in complex multi-seller environments with violations of the Stable Unit Treatment Value Assumption (SUTVA). We identify two critical challenges: Seller-level Cannibalization, where incentives shift expenditure between shops without growing the platform, and Incentive-level Cannibalization, where organic conversi

Record details

Published: 6 July 2026
Source: arXiv
Category: Research
Topics: Environment
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (6 July 2026), “CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling,” evidence record 191, https://ethics.ai/record/191 (originally published by arXiv).

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